This invention relates generally to the allocation (e.g. as in a market or exchange) of the supply of a class of products / services with the demand for a class of products / services in an optimal manner (i.e. system-wide best solution since the values of different allocation strategies may vary significantly) that quantifies and accounts for the uncertainty surrounding the supply and demand of different products / services. More particularly, the present invention comprises a system and method for the optimal placement of ads on Web pages.
Optimal ad placement has become a critical competitive advantage in the Internet advertising business. Consumers are spending an ever-increasing amount of time online looking for information. The information, provided by Internet content providers, is viewed on a page-by-page basis. Each page can contain written and graphical information as well as one or more ads. Key advantages of the Internet, relative to other information media, are that each page can be customized to fit a customer profile and ads can contain links to other Internet pages. Thus, ads can be directly targeted at different customer segments and the ads themselves are direct connections to well-designed Internet pages. Although the present example has been described with respect to traditional Web browsing on a Web page, the same principals apply for any content, including information or messages, as well as advertisements, delivered over any Internet enabled distribution channel, such as via e-mail, wireless devices (including, but not limited to phones, pagers, PDAs, desktop displays, and digital billboards), or other media, such as ATM terminals.
Therefore, as used herein, the term “ad” is also meant to include any content, including information or messages, as well as advertisements, such as, but not limited to, Web banners, product offerings, special non-commercial or commercial messages, or any other sort of displayed or audio information.
The terms “Web page,” “Web site,” and “site” are meant to include any sort of information display or presentation over an Internet enabled distribution channel that may have customizable areas (including the entire area) and may be visual, audio, or both. They may be segmented and or customized by factors such as time and location. The term “Internet browser” is any means that decodes and displays the above-defined Web pages or sites, whether by software, hardware, or utility, including diverse means not typically considered as a browser, such as games.
The term “Internet” is meant to include all TCP/IP based communication channels, without limitation to any particular communication protocol or channel, including, but not limited to, e-mail, News via NNTP, and the WWW via HTTP and WAP (using, e.g., HTML, DHTML, XHTML, XML, SGML, VRML, ASP, CGI, CSS, SSI, Flash, Java, JaysScript, Perl, Python, Rexx, SMIL, Tcl, VBScript, HDML, WML, WMLScript, etc.).
The term “customer” or “user” refers to any consumer, viewer, or visitor of the above-defined Web pages or sites and can also refer to the aggregation of individual customers into certain groupings. “Clicks” and “click-thru-rate” or “CTR” refers to any sort of definable, trackable, and/or measurable action or response that can occur via the Internet and can include any desired action or reasonable measure of performance activity by the customer, including, but not limited to, mouse clicks, impressions delivered, sales generated, and conversions from visitors to buyers. Additionally, references to customers “viewing” ads is meant to include any presentation, whether visual, aural, or a combination thereof.
The term “revenue” refers to any meaningful measure of value, including, but not limited to, revenue, profits, expenses, customer lifetime value, and net present value (NPV).
The Internet ad placement technology of the present invention provides an optimal strategic framework for selecting which ad a customer will view next. It maximizes the overall expected ad placement revenue (or any other measure of value), trading off the desire for learning with revenue generation. The technology can be executed in “real-time” and updates the strategy space for every customer.
At its core, the problem is to place the right ad to the right customer. Ad placements are compensated based on the number of successful responses that they generate. This usually means that compensation occurs every time a customer responds to (e.g., clicks) an ad. Customers respond to ads according to their interests and demands. Thus, a key necessity is to obtain a reliable characteristic profile of each customer. Only with given information about the customer can ads be provided that are targeted towards each customer. Second, there is a need to estimate how different customers will react to different ads. That is, a customer-ad response relation is required. Finally, there is a need for an ad placement technology that optimally decides which ad to show. At the instant a customer opens a page, it is necessary to place an ad. The ad placement technology must incorporate the customer's likely response to each ad and the financial gains resulting from a customer's selection of an ad.
A successful ad placement technology must overcome several critical complications. First, the ad placement algorithm must be sufficiently fast to ensure “real-time” placement. Second, a key element of the technology is its ability to learn through continuous updating. Little information is available about new ads. However, as ads are placed, it can be learned how they relate to various customer profiles. Thus, the technology should both be able to learn and trade off learning versus revenue generation. Finally, the ad placement technology must be able to detect ineffective ads and incorporate minimum and maximum ad placement and ad selection constraints.